Senior Data Scientist, Borrowell

• 5+ years of experience delivering data science and machine learning solutions with demonstrated ownership of high-impact production models from problem definition through production and iteration
• Hands-on experience designing, building, and iterating on ranking, recommendation, or personalization models used in a production environment (e.g., offer ranking, next-best-action, feed ranking, eligibility routing)
• Strong proficiency in Python for data analysis, feature engineering, and modeling
• Advanced SQL skills, including complex joins and analytical queries across large datasets
• Deep experience with supervised learning, including handling class imbalance and model calibration
• Strong background in experimentation and A/B testing, including metric design, offline/online evaluation and interpretation
• Excellent communication skills — able to clearly explain complex models, trade-offs, and impact to technical and non-technical audiences
• Comfortable owning ambiguous problems end-to-end and driving alignment across stakeholders in fast-moving environments

Desirable

• As a Senior Data Scientist, you will play a critical role in shaping and delivering Borrowell’s core machine learning capabilities and influencing product direction through data-driven recommendations
• You will partner closely with Product, Business, Data, and Engineering leaders to design, build, and scale ML-driven systems that personalize the member experience, power our recommendation and ranking engines, and directly impact marketplace conversion and approval outcomes
• This is a hands-on, product-facing role with end-to-end ownership — from problem framing and model design to experimentation, measurement, and iteration in production
• This role is expected to operate as a technical leader, setting modeling direction and raising the bar for data science rigor across the organization
• During your first year, you can expect to:
• Own high-impact ML initiatives technical and product trade-off decisions – Lead the design and delivery of product ranking, intent prediction, and approval likelihood models that materially improve business KPIs
• Translate strategy into models – Work with Product and Business stakeholders to convert complex business goals into well-defined ML problems, success metrics, and experimentation plans
• Build, evaluate, and iterate on production models – Develop robust features, train and calibrate models, and continuously improve performance through rigorous evaluation and A/B testing
• Drive measurable business outcomes – Connect model performance to conversion, approval rates, revenue, and member engagement, and clearly communicate impact to stakeholders
• Establish best practices for experimentation and modeling – Raise the bar on model evaluation, calibration, drift analysis, and offline/online alignment

• Please note that due to the sensitive nature of the work we do, clearing a credit and criminal record check is a condition of employment